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Artificial Intelligence for Robotics

You're reading from   Artificial Intelligence for Robotics Build intelligent robots using ROS 2, Python, OpenCV, and AI/ML techniques for real-world tasks

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781805129592
Length 344 pages
Edition 2nd Edition
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Author (1):
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Francis X. Govers III Francis X. Govers III
Author Profile Icon Francis X. Govers III
Francis X. Govers III
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Table of Contents (18) Chapters Close

Preface 1. Part 1: Building Blocks for Robotics and Artificial Intelligence
2. Chapter 1: The Foundation of Robotics and Artificial Intelligence FREE CHAPTER 3. Chapter 2: Setting Up Your Robot 4. Chapter 3: Conceptualizing the Practical Robot Design Process 5. Part 2: Adding Perception, Learning, and Interaction to Robotics
6. Chapter 4: Recognizing Objects Using Neural Networks and Supervised Learning 7. Chapter 5: Picking Up and Putting Away Toys using Reinforcement Learning and Genetic Algorithms 8. Chapter 6: Teaching a Robot to Listen 9. Part 3: Advanced Concepts – Navigation, Manipulation, Emotions, and More
10. Chapter 7: Teaching the Robot to Navigate and Avoid Stairs 11. Chapter 8: Putting Things Away 12. Chapter 9: Giving the Robot an Artificial Personality 13. Chapter 10: Conclusions and Reflections 14. Answers 15. Index 16. Other Books You May Enjoy Appendix

Recognizing Objects Using Neural Networks and Supervised Learning

This is the chapter where we’ll start to combine robotics and artificial intelligence (AI) to accomplish some of the tasks we laid out so carefully in previous chapters. The subject of this chapter is object recognition – we will be teaching the robot to recognize what a toy is so that it can then decide what to pick up and what to leave alone. We will be using convolutional neural networks (CNNs) as machine learning tools for separating objects in images, recognizing them, and locating them in the camera frame so that the robot can then locate them. More specifically, we’ll be using images to recognize objects. We’ll be taking a picture and then looking to see whether the computer recognizes specific types of objects in those pictures. We won’t be recognizing objects themselves, but rather images or pictures of objects. We’ll also be putting bounding boxes around objects, separating...

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